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Journal of Computer Networks and Communications
Volume 2019, Article ID 1306491, 6 pages
https://doi.org/10.1155/2019/1306491
Research Article

Performance of OFDM: FSO Communication System with Hybrid Channel Codes during Weak Turbulence

1ECE, IKGPTU, Research Scholar, Jalandhar 144601, India
2ECE, IEEE Life Sr. Member, RIET, Abohar 152116, USA
3ECE, UIET-PU, Chandigarh 160016, India

Correspondence should be addressed to Ritu Gupta; moc.liamg@20atpugutirre

Received 31 August 2018; Accepted 21 January 2019; Published 7 February 2019

Academic Editor: Peter Mueller

Copyright © 2019 Ritu Gupta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The performance of orthogonal frequency division multiplexing- (OFDM-) based free-space optics (FSO) depends on various parameters such as number of subcarriers, base band modulation, nature of laser beam, turbulence modelling, and much more. Various diversity techniques have been studied by researchers for the improvement of signal strength due to fading caused by atmospheric turbulence. In this paper, a novel channel coding scheme formed by serially concatenation of irregular low-density parity check (LDPC) and trellis code modulation (TCM) codes linked by interleaver is proposed. The proposed unified coding scheme is simulated and analyzed using the lognormal scintillation model, which is suitable for weak turbulent conditions. The obtained results are the comparative study of various channel coding schemes in terms of bit error rate (BER) vs. signal-to-noise ratio (SNR). Simulation results confirm that newly designed hybrid code outperforms the independently coded and uncoded systems under weak turbulence conditions by reducing the number of errors in the transmitted information that occurs due to fading. It is found that the presented hybrid coded OFDM-FSO system with 16-level quadrature amplitude modulation (QAM) provides significant improvement with less decoding complexity and reasonable delay.